Fine-scale differentiation between Bacillus anthracis and Bacillus cereus group signatures in metagenome shotgun data.
Identifieur interne : 000911 ( PubMed/Checkpoint ); précédent : 000910; suivant : 000912Fine-scale differentiation between Bacillus anthracis and Bacillus cereus group signatures in metagenome shotgun data.
Auteurs : Robert A. Petit Iii [États-Unis] ; James M. Hogan [Australie] ; Matthew N. Ezewudo [États-Unis] ; Sandeep J. Joseph [États-Unis] ; Timothy D. Read [États-Unis]Source :
- PeerJ [ 2167-8359 ] ; 2018.
Abstract
It is possible to detect bacterial species in shotgun metagenome datasets through the presence of only a few sequence reads. However, false positive results can arise, as was the case in the initial findings of a recent New York City subway metagenome project. False positives are especially likely when two closely related are present in the same sample. Bacillus anthracis, the etiologic agent of anthrax, is a high-consequence pathogen that shares >99% average nucleotide identity with Bacillus cereus group (BCerG) genomes. Our goal was to create an analysis tool that used k-mers to detect B. anthracis, incorporating information about the coverage of BCerG in the metagenome sample.
DOI: 10.7717/peerj.5515
PubMed: 30155371
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Hogan</name><affiliation wicri:level="1"><nlm:affiliation>Queensland University of Technology, Brisbane, Australia.</nlm:affiliation><country xml:lang="fr">Australie</country><wicri:regionArea>Queensland University of Technology, Brisbane</wicri:regionArea><wicri:noRegion>Brisbane</wicri:noRegion></affiliation></author><author><name sortKey="Ezewudo, Matthew N" sort="Ezewudo, Matthew N" uniqKey="Ezewudo M" first="Matthew N" last="Ezewudo">Matthew N. Ezewudo</name><affiliation wicri:level="2"><nlm:affiliation>Department of Medicine, Division of Infectious Diseases, Emory University School of Medicine, Atlanta, GA, United States of America.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Medicine, Division of Infectious Diseases, Emory University School of Medicine, Atlanta, GA</wicri:regionArea><placeName><region type="state">Géorgie (États-Unis)</region></placeName></affiliation></author><author><name sortKey="Joseph, Sandeep J" sort="Joseph, Sandeep J" uniqKey="Joseph S" first="Sandeep J" last="Joseph">Sandeep J. Joseph</name><affiliation wicri:level="2"><nlm:affiliation>Department of Medicine, Division of Infectious Diseases, Emory University School of Medicine, Atlanta, GA, United States of America.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Medicine, Division of Infectious Diseases, Emory University School of Medicine, Atlanta, GA</wicri:regionArea><placeName><region type="state">Géorgie (États-Unis)</region></placeName></affiliation></author><author><name sortKey="Read, Timothy D" sort="Read, Timothy D" uniqKey="Read T" first="Timothy D" last="Read">Timothy D. 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Petit Iii</name><affiliation wicri:level="2"><nlm:affiliation>Department of Medicine, Division of Infectious Diseases, Emory University School of Medicine, Atlanta, GA, United States of America.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Medicine, Division of Infectious Diseases, Emory University School of Medicine, Atlanta, GA</wicri:regionArea><placeName><region type="state">Géorgie (États-Unis)</region></placeName></affiliation></author><author><name sortKey="Hogan, James M" sort="Hogan, James M" uniqKey="Hogan J" first="James M" last="Hogan">James M. Hogan</name><affiliation wicri:level="1"><nlm:affiliation>Queensland University of Technology, Brisbane, Australia.</nlm:affiliation><country xml:lang="fr">Australie</country><wicri:regionArea>Queensland University of Technology, Brisbane</wicri:regionArea><wicri:noRegion>Brisbane</wicri:noRegion></affiliation></author><author><name sortKey="Ezewudo, Matthew N" sort="Ezewudo, Matthew N" uniqKey="Ezewudo M" first="Matthew N" last="Ezewudo">Matthew N. Ezewudo</name><affiliation wicri:level="2"><nlm:affiliation>Department of Medicine, Division of Infectious Diseases, Emory University School of Medicine, Atlanta, GA, United States of America.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Medicine, Division of Infectious Diseases, Emory University School of Medicine, Atlanta, GA</wicri:regionArea><placeName><region type="state">Géorgie (États-Unis)</region></placeName></affiliation></author><author><name sortKey="Joseph, Sandeep J" sort="Joseph, Sandeep J" uniqKey="Joseph S" first="Sandeep J" last="Joseph">Sandeep J. Joseph</name><affiliation wicri:level="2"><nlm:affiliation>Department of Medicine, Division of Infectious Diseases, Emory University School of Medicine, Atlanta, GA, United States of America.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Medicine, Division of Infectious Diseases, Emory University School of Medicine, Atlanta, GA</wicri:regionArea><placeName><region type="state">Géorgie (États-Unis)</region></placeName></affiliation></author><author><name sortKey="Read, Timothy D" sort="Read, Timothy D" uniqKey="Read T" first="Timothy D" last="Read">Timothy D. Read</name><affiliation wicri:level="2"><nlm:affiliation>Department of Medicine, Division of Infectious Diseases, Emory University School of Medicine, Atlanta, GA, United States of America.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Medicine, Division of Infectious Diseases, Emory University School of Medicine, Atlanta, GA</wicri:regionArea><placeName><region type="state">Géorgie (États-Unis)</region></placeName></affiliation></author></analytic><series><title level="j">PeerJ</title><idno type="ISSN">2167-8359</idno><imprint><date when="2018" type="published">2018</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">It is possible to detect bacterial species in shotgun metagenome datasets through the presence of only a few sequence reads. However, false positive results can arise, as was the case in the initial findings of a recent New York City subway metagenome project. False positives are especially likely when two closely related are present in the same sample. <i>Bacillus anthracis</i>, the etiologic agent of anthrax, is a high-consequence pathogen that shares >99% average nucleotide identity with <i>Bacillus cereus</i> group (BCerG) genomes. Our goal was to create an analysis tool that used k-mers to detect <i>B. anthracis,</i> incorporating information about the coverage of BCerG in the metagenome sample.</div></front></TEI><pubmed><MedlineCitation Status="PubMed-not-MEDLINE" Owner="NLM"><PMID Version="1">30155371</PMID><DateRevised><Year>2019</Year><Month>11</Month><Day>20</Day></DateRevised><Article PubModel="Electronic-eCollection"><Journal><ISSN IssnType="Print">2167-8359</ISSN><JournalIssue CitedMedium="Print"><Volume>6</Volume><PubDate><Year>2018</Year></PubDate></JournalIssue><Title>PeerJ</Title><ISOAbbreviation>PeerJ</ISOAbbreviation></Journal><ArticleTitle>Fine-scale differentiation between <i>Bacillus anthracis</i> and <i>Bacillus cereus</i> group signatures in metagenome shotgun data.</ArticleTitle><Pagination><MedlinePgn>e5515</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.7717/peerj.5515</ELocationID><Abstract><AbstractText Label="Background" NlmCategory="UNASSIGNED">It is possible to detect bacterial species in shotgun metagenome datasets through the presence of only a few sequence reads. However, false positive results can arise, as was the case in the initial findings of a recent New York City subway metagenome project. False positives are especially likely when two closely related are present in the same sample. <i>Bacillus anthracis</i>, the etiologic agent of anthrax, is a high-consequence pathogen that shares >99% average nucleotide identity with <i>Bacillus cereus</i> group (BCerG) genomes. Our goal was to create an analysis tool that used k-mers to detect <i>B. anthracis,</i> incorporating information about the coverage of BCerG in the metagenome sample.</AbstractText><AbstractText Label="Methods" NlmCategory="UNASSIGNED">Using public complete genome sequence datasets, we identified a set of 31-mer signatures that differentiated <i>B. anthracis</i> from other members of the <i>B. cereus</i> group (BCerG), and another set which differentiated BCerG genomes (including <i>B. anthracis</i>) from other <i>Bacillus</i> strains. We also created a set of 31-mers for detecting the lethal factor gene, the key genetic diagnostic of the presence of anthrax-causing bacteria. We created synthetic sequence datasets based on existing genomes to test the accuracy of a k-mer based detection model.</AbstractText><AbstractText Label="Results" NlmCategory="UNASSIGNED">We found 239,503 <i>B. anthracis</i>-specific 31-mers (the <i>Ba31 set</i>), 10,183 BCerG 31-mers (the <i>BCerG31 set</i>), and 2,617 lethal factor k-mers (the <i>lef31</i> set). We showed that false positive <i>B. anthracis</i> k-mers-which arise from random sequencing errors-are observable at high genome coverages of <i>B. cereus</i>. We also showed that there is a "gray zone" below 0.184× coverage of the <i>B. anthracis</i> genome sequence, in which we cannot expect with high probability to identify lethal factor k-mers. We created a linear regression model to differentiate the presence of <i>B. anthracis</i>-like chromosomes from sequencing errors given the BCerG background coverage. We showed that while shotgun datasets from the New York City subway metagenome project had no matches to <i>lef31</i> k-mers and hence were negative for <i>B. anthracis</i>, some samples showed evidence of strains very closely related to the pathogen.</AbstractText><AbstractText Label="Discussion" NlmCategory="UNASSIGNED">This work shows how extensive libraries of complete genomes can be used to create organism-specific signatures to help interpret metagenomes. We contrast "specialist" approaches to metagenome analysis such as this work to "generalist" software that seeks to classify all organisms present in the sample and note the more general utility of a k-mer filter approach when taxonomic boundaries lack clarity or high levels of precision are required.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Petit Iii</LastName><ForeName>Robert A</ForeName><Initials>RA</Initials><AffiliationInfo><Affiliation>Department of Medicine, Division of Infectious Diseases, Emory University School of Medicine, Atlanta, GA, United States of America.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Hogan</LastName><ForeName>James M</ForeName><Initials>JM</Initials><AffiliationInfo><Affiliation>Queensland University of Technology, Brisbane, Australia.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Ezewudo</LastName><ForeName>Matthew N</ForeName><Initials>MN</Initials><AffiliationInfo><Affiliation>Department of Medicine, Division of Infectious Diseases, Emory University School of Medicine, Atlanta, GA, United States of America.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Joseph</LastName><ForeName>Sandeep J</ForeName><Initials>SJ</Initials><AffiliationInfo><Affiliation>Department of Medicine, Division of Infectious Diseases, Emory University School of Medicine, Atlanta, GA, United States of America.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Read</LastName><ForeName>Timothy D</ForeName><Initials>TD</Initials><AffiliationInfo><Affiliation>Department of Medicine, Division of Infectious Diseases, Emory University School of Medicine, Atlanta, GA, United States of America.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2018</Year><Month>08</Month><Day>22</Day></ArticleDate></Article><MedlineJournalInfo><Country>United States</Country><MedlineTA>PeerJ</MedlineTA><NlmUniqueID>101603425</NlmUniqueID><ISSNLinking>2167-8359</ISSNLinking></MedlineJournalInfo><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">Anthrax</Keyword><Keyword MajorTopicYN="N">Bacillus anthracis</Keyword><Keyword MajorTopicYN="N">Bacillus cereus group</Keyword><Keyword MajorTopicYN="N">Metagenome</Keyword><Keyword MajorTopicYN="N">Typing</Keyword><Keyword MajorTopicYN="N">k-mer</Keyword></KeywordList><CoiStatement>Timothy D. Read is an Academic Editor for PeerJ.</CoiStatement></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2018</Year><Month>06</Month><Day>07</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2018</Year><Month>08</Month><Day>03</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2018</Year><Month>8</Month><Day>30</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2018</Year><Month>8</Month><Day>30</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2018</Year><Month>8</Month><Day>30</Day><Hour>6</Hour><Minute>1</Minute></PubMedPubDate></History><PublicationStatus>epublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">30155371</ArticleId><ArticleId IdType="doi">10.7717/peerj.5515</ArticleId><ArticleId IdType="pii">5515</ArticleId><ArticleId IdType="pmc">PMC6109372</ArticleId></ArticleIdList><ReferenceList><Reference><Citation>Cell Syst. 2015 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